- Add reply_to_post for threaded conversations
- Add post_with_rich_text for clickable links and mentions
- Add quote_post for sharing with commentary
- Add post_with_images for visual content (up to 4 images)
- Update types with new response structures
- Add httpx dependency for image downloads
- Document AI assistant use cases in README
- Fix follow_user to use params dict for search_actors API
- Add CID fetching for like_post (required by atproto API)
- Add CID fetching for repost (required by atproto API)
- Both like and repost now fetch the post first to get its CID
- Add TypedDict definitions for all responses in types.py
- Convert read operations to resources (status, timeline, search, notifications)
- Keep state-modifying operations as tools (post, follow, like, repost)
- Add proper type annotations with Annotated and Field descriptions
- Update demo to use read_resource for resources
- Better separation of concerns with typed interfaces
- Create _atproto.py module for private implementation details
- Clean server.py to only expose public API (tools)
- Update demo with --post flag instead of comments
- Better separation of concerns
- Add pydantic_core.to_json() serialization for non-string prompt arguments
- Update type annotations to accept dict[str, Any] instead of dict[str, str]
- Add focused tests covering specific scenarios:
* Client always serializes non-string args regardless of server types
* Integration with server-side type conversion
* Client serialization error with specific PydanticSerializationError
* Server deserialization error with specific McpError match
This ensures MCP protocol compliance while maintaining developer experience
with typed arguments.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
Add proper null checks and type assertions for prompt argument
handling in tests to satisfy pyright strict typing.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
Change from 'Arguments must be strings conforming to this JSON schema'
to 'Provide as a JSON string matching the following schema' for clearer
instruction to LLMs about string format requirements.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Fix ValueError -> PromptError for consistent error handling
- Add automatic JSON schema descriptions to non-string prompt arguments
- Include comprehensive tests for argument description enhancement
- Verify enhanced descriptions are visible via MCP protocol
This helps developers understand the expected string format for complex
types when calling prompts from MCP clients.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
Updated FunctionPrompt.render() to accept dict[str, Any] instead of
dict[str, str | Context] to preserve the developer experience of
passing properly typed arguments while also supporting string-only
arguments from MCP clients.
The _convert_string_arguments method now intelligently handles both
scenarios:
- Already-typed arguments are passed through unchanged
- String arguments are converted to expected types when needed
This maintains backward compatibility while enabling MCP spec compliance.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
